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If deep learning is the answer, what is the question?

Journal article

Saxe A. et al, (2021), Nat Rev Neurosci, 22, 55 - 67

A Critique of Pure Hierarchy: Uncovering Cross-Cutting Structure in a Natural Dataset

Journal article

SAXE A., (2020), Neurocomputational Models of Cognitive Development and Processing

Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup

Journal article

Goldt S. et al, (2020), ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), 32

Energy-entropy competition and the effectiveness of stochastic gradient descent in machine learning

Journal article

Zhang Y. et al, (2020), Molecular Physics: An International Journal at the Interface Between Chemistry and Physics

Hierarchy Through Composition with Multitask LMDPs

Conference paper

SAXE A., (2020)

High-dimensional dynamics of generalization error in neural networks

Journal article

SAXE A. and Advani M., (2020), Arxiv

On the information bottleneck theory of deep learning

Journal article

Saxe AM. et al, (2019), Journal of Statistical Mechanics: Theory and Experiment, 2019

A deep learning framework for neuroscience

Journal article

SAXE A. and BOGACZ R., (2019), Nature Neuroscience

A mathematical theory of semantic development in deep neural networks.

Journal article

Saxe AM. et al, (2019), Proc Natl Acad Sci U S A, 116, 11537 - 11546

Tensor Switching Networks

Conference paper

Tsai C-Y. et al, (2016), ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 29 (NIPS 2016), 29

Acquisition of decision making criteria: reward rate ultimately beats accuracy.

Journal article

Balci F. et al, (2011), Atten Percept Psychophys, 73, 640 - 657